Introduction

Hi Robert, here is my reproducible analysis concerning the Gapminder dataset!

Get data

The data are included in the gapminder library

library(gapminder)
head(gapminder)

##       country continent year lifeExp      pop gdpPercap
## 1 Afghanistan      Asia 1952  28.801  8425333  779.4453
## 2 Afghanistan      Asia 1957  30.332  9240934  820.8530
## 3 Afghanistan      Asia 1962  31.997 10267083  853.1007
## 4 Afghanistan      Asia 1967  34.020 11537966  836.1971
## 5 Afghanistan      Asia 1972  36.088 13079460  739.9811
## 6 Afghanistan      Asia 1977  38.438 14880372  786.1134

We work on 2012 only:

data=subset(gapminder, year==2007)

Make the plot

# Basic ggplot2 chart
library(ggplot2)
p=ggplot(data, 
  aes(gdpPercap, lifeExp, size = pop, color = continent, frame = year)) +
  geom_point()
# Made interactive with plotly
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

ggplotly(p)